Piecewise Linear and Stochastic Models for the Analysis of Cyber Resilience
Piecewise Linear and Stochastic Models for the Analysis of Cyber Resilience
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用于网络弹性分析的分段线性和随机模型
DOI：
10.1109/ciss56502.2023.10089725
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Vandekerckhove, Joachim
中科院分区：
文献类型：
--
作者：
Weisman, Michael J.;Kott, Alexander;Vandekerckhove, Joachim
我们模拟了一辆配备自主网络防御系统的车辆，除了其固有的物理弹性功能。当受到攻击时，这种网络物理特征的集合（即，“bonware”）努力抵抗恶意软件的攻击所导致的性能下降并从中恢复。我们的模型的基本微分方程管理这种攻击的恶意软件和bonware的分段线性特征，开发一个离散时间随机模型，并表明，平均值的实例化的随机模型近似解的连续微分方程。我们开发了一个理论和方法来近似与这些方程相关的参数。
We model a vehicle equipped with an autonomous cyber-defense system in addition to its inherent physical resilience features. When attacked, this ensemble of cyber-physical features (i.e., “bonware”) strives to resist and recover from the performance degradation caused by the malware's attack. We model the underlying differential equations governing such attacks for piecewise linear characterizations of malware and bonware, develop a discrete time stochastic model, and show that averages of instantiations of the stochastic model approximate solutions to the continuous differential equation. We develop a theory and methodology for approximating the parameters associated with these equations.
要提高网络弹性，请对其进行衡量
影响因子：
2.2
作者：
A. Kott;I. Linkov
通讯作者：
I. Linkov